Module manager: Xanthe Whittaker
Email: X.Whittaker@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2026/27
This module is not approved as an Elective
The world of business is shaped by data. Modern organisations use diverse data sources to understand performance, workforce dynamics and patterns of human behaviour. This module introduces you to the core principles of analytics within the field of human resource management. Grounded in cutting edge academic research and practical examples from the large organisations including national health services and global leading enterprises, the module develops your ability to confidently engage with quantitative HR data and translate analytical outputs into meaningful, evidence-based insights. You will gain hands-on experience in how analytics is used in real-world contexts to address challenges such as workforce planning, performance management and employee wellbeing By the end of the module, you will build the analytical literacy and data communication skills increasingly demanded by employers.
The key objective of the module is:
1. to develop students’ capacity to use cutting-edge analytical tools to address strategic people management challenges in organisations;
2. to develop students’ understanding of how different analytical methods can be used in an organisational context;
3. to develop students’ abilities to translate analytical findings into actionable management insights.
Upon completion of this module, students will be able to:
1. Evaluate the rationales, fundamental principles and theoretical underpinnings of analytics in the context of human resource management.
2. Synthesise debates about the types of HR outcomes and common analytical perspectives in HRM.
3. Utilise and apply different types of HR data.
4. Critically evaluate analytical outputs and their limitations.
On successful completion of the module students will be able to:
1. Digital, technical: Critically analyse and interrogate organisational HR datasets and analytical outputs, assessing their robustness, assumptions, limitations and implications for managerial practice.
2. Academic, sustainability: Formulate evidence-based and ethically informed recommendations for people management challenges by synthesising analytical findings with organisational contexts.
3. Work-ready: Communicate complex analytical insights clearly and persuasively in written and oral formats to both specialist and non-specialist audiences.
4. Enterprise: Work effectively in teams to interpret data, evaluate alternative analytical approaches, and develop coherent and defensible management insights.
Indicative content:
- Analytics in the context of HRM: what is analytics, and how can analytics be applied to HR and human capital?
- Strategy and analytics involving strategic human capital theory, strategic management, evidence-based management and critical evaluation of these concepts.
- Understanding HR data: data generation and administration; classes of data involving attitudinal data, soft performance data and hard performance outcomes.
- Introduction to the principles of statistical modelling and predictive analytics and how these can be used to gain insights into employee engagement, attrition, performance and other key human resource indicators.
- The ethics and future of people analytics
- Responsible analytics, analytics as craft, analytics and automation.
| Delivery type | Number | Length hours | Student hours |
|---|---|---|---|
| Practical | 5 | 2 | 10 |
| Seminar | 5 | 2 | 10 |
| Private study hours | 130 | ||
| Total Contact hours | 20 | ||
| Total hours (100hr per 10 credits) | 150 | ||
Students will receive formative feedback as part of personal tutorials and independent analytical tasks conducted on the basis of the material covered in workshops and seminars. The feedback will be written, helping students to improve their analytical and report writing skills.
| Assessment type | Notes | % of formal assessment |
|---|---|---|
| Practical Report | A 3,000-word report based on people analytics case-studies in specific organisational settings | 100 |
| Total percentage (Assessment Coursework) | 100 | |
The resit for this module will be 100% by 3,000-word analytics report.
Check the module area in Minerva for your reading list
Last updated: 30/04/2026
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